Relevance Feedback in Content Based Image Retrieval: A Review

This paper provides an overview of the technical achievements in the research area of relevance feedback (RF) in content-based image retrieval (CBIR). Relevance feedback is a powerful technique in CBIR systems, in order to improve the performance of CBIR effectively. It is an open research area to the researcher to reduce the semantic gap between low-level features and high level concepts. The paper covers the current state of art of the research in relevance feedback in CBIR, various relevance feedback techniques and issues in relevance feedback are discussed in detail

M-Band Wavelet based Texture Features for Content Based Image Retrieval

Biorthonormal M-band wavelet transform is used to decompose the image into M × M sub-bands for constructing the feature database in content-based image retrieval of 1856 Brodatz texture images. Texture features are obtained by computing the measure of energy, standard deviation and its combination on each band. Results are far superior and impressive than conventional two-band wavelet decomposition. Keywords: M-band wavelet, 2-band wavelet, Content-based image retrieval, image database, feature database, similarity, query image, texture analysis. 1.Introduction: Worldwide networking allows us to communicate, share, and learn information in th